Mathematics education for STEM as place
Bibliographic record
Abstract
Abstract Positioned within Indigenous and ecological discourses, our paper reconsiders human-centered relationships with earth and activities such as STEM that view earth as commodity, resource, and platform. In doing so, we turn to the ways earth (e.g., rivers, forests, animals) teaches mathematics education for STEM as place and reveals intelligences that exceed those of humankind. Using examples of place and land, we illustrate how such a conception contrasts with current calls and goals for STEM and integrated STEM education. We contend that comprehending STEM as place renews potential for success to be defined “as the continuity of life”; that is, all that concerns the natural world, including human wellbeing in general, and in particular mathematics and mathematics education. To conclude, we propose research directions to study mathematical ways of being, mathematics, and mathematics education for STEM as place. We include possible implications and pathways for such work which prompts (re)visioning and (re)enacting mathematics education to be for STEM as place.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".